Geology topics

Daniel Bruce Fitzgerald

Publications and source records attributed to Daniel Bruce Fitzgerald.

5 recordsLinked to original sources

USGS2022

Multispecies approaches to status assessments in support of endangered species classifications

Multispecies risk assessments have developed within many international conservation programs, reflecting a widespread need for efficiency. Under the United States Endangered Species Act (ESA), multispecies assessments ultimately lead to species-level listing decisions. Although this approach provides opportunities for improved efficiency, it also risks overwhelming or biasing the assessment process and would benefit from clear guidance for practitioners. We reviewed multispecies assessments conducted between 1993 and 2019 for ESA listing decisions to identify the ecological basis for combining species, the assessment approach used, and the policy factors influencing their efficacy. We identified 42 cases covering 359 species. Most assessments (81%) included two to five species, although the maximum was 82. A common theme involved grouping narrow endemics or habitat specialists based on taxonomic relatedness, similar distributions, and common threats to persistence. All assessments included a combined threats analysis, but few employed a common species' response model or expert elicitation process. Although ESA risk assessments are distinct from policy decisions, most assessments (50%) supported decisions that all species warranted endangered status. Available guidance has generally emphasized ecological similarity as the key attribute leading to successful multispecies assessments. The challenge with consistently selecting species based on qualitative proxies such as common distributions or threats to persistence is that ecological patterns and processes are scale dependent. Focusing instead on the assessment methods and their potential for bias and increased efficiency may provide a stronger basis for developing consistent and transparent guidance.

Conservation Science and Practice↗

USGS2021

Genetic and morphological characterization of the freshwater mussel clubshell species complex (Pleurobema clava and Pleurobema oviforme) to inform conservation planning

The shell morphologies of the freshwater mussel species Pleurobema clava (federally endangered) and Pleurobema oviforme (species of concern) are similar, causing considerable taxonomic confusion between the two species over the last 100 years. While P. clava was historically widespread throughout the Ohio River basin and tributaries to the lower Laurentian Great Lakes, P. oviforme was confined to the Tennessee and the upper Cumberland River basins. We used two mitochondrial DNA (mtDNA) genes, 13 novel nuclear DNA microsatellite markers, and shell morphometrics to help resolve this taxonomic confusion. Evidence for a single species was apparent in phylogenetic analyses of each mtDNA gene, revealing monophyletic relationships with minimal differentiation and shared haplotypes. Analyses of microsatellites showed significant genetic structuring, with four main genetic clusters detected, respectively, in the upper Ohio River basin, the lower Ohio River and Great Lakes, and upper Tennessee River basin, and a fourth genetic cluster, which included geographically intermediate populations in the Ohio and Tennessee river basins. While principal components analysis (PCA) of morphometric variables (i.e., length, height, width, and weight) showed significant differences in shell shape, only 3% of the variance in shell shape was explained by nominal species. Using Linear Discriminant and Random Forest (RF) analyses, correct classification rates for the two species' shell forms were 65.5% and 83.2%, respectively. Random Forest classification rates for some populations were higher; for example, for North Fork Holston (HOLS), it was >90%. While nuclear DNA and shell morphology indicate that the HOLS population is strongly differentiated, perhaps indicative of cryptic biodiversity, we consider the presence of a single widespread species the most likely biological scenario for many of the investigated populations based on our mtDNA dataset. However, additional sampling of P. oviforme populations at nuclear loci is needed to corroborate this finding.

Indiana, Kentucky, Ohio, Pennsylvania, Tennessee, ↗

USGS2021

How do lizard niches conserve, diverge or converge? Further exploration of saurian evolutionary ecology

Environmental conditions on Earth are repeated in non-random patterns that often coincide with species from different regions and time periods having consistent combinations of morphological, physiological and behavioral traits. Observation of repeated trait combinations among species confronting similar environmental conditions suggest that adaptive trait combinations are constrained by functional tradeoffs within or across niche dimensions. In an earlier study, we assembled a high-resolution database of functional traits for 134 lizard species to explore ecological diversification in relation to five fundamental niche dimensions. Here we expand and further examine multivariate relationships in that dataset to assess the relative influence of niche dimensions on the distribution of species in 6-dimensional niche space and how these may deviate from distributions generated from null models. We then analyzed a dataset with lower functional-trait resolution for 1023 lizard species that was compiled from our dataset and a published database, representing most of the extant families and environmental conditions occupied by lizards globally. Ordinations from multivariate analysis were compared with null models to assess how ecological and historical factors have resulted in the conservation, divergence or convergence of lizard niches.

BMC Ecology and Evolution↗

USGS2021

Using expert knowledge to support Endangered Species Act decision‐making for data‐deficient species

Many questions relevant to conservation decision making are characterized by extreme uncertainty due to lack of empirical data and complexity of the underlying ecological processes, leading to a rapid increase in the use of structured protocols to elicit expert knowledge. Published ecological applications often employ a modified Delphi method, where experts provide judgments anonymously and mathematical aggregation techniques are used to combine judgments. The Sheffield Elicitation Framework (SHELF) differs in its behavioral approach to synthesizing individual judgments into a fully specified probability distribution for an unknown quantity. This study demonstrates the remote use of the SHELF protocol for an extinction risk assessment of three subterranean aquatic species petitioned for listing under the US Endangered Species Act. Experts were provided an empirical threat assessment for each known locality using video conferencing and asked for judgments on the probability of population persistence over four generations using online submission forms and R‐shiny apps available through the SHELF package. Despite large uncertainty for all populations, results reveal key differences between species’ risk of extirpation based on spatial variation in dominant threats, local land use and management practices, and microhabitat use. The resulting probability distributions provide decision makers with a full picture of uncertainty that is consistent with the probabilistic nature of risk assessments, and discussions during the behavioral aggregation stage clearly document dominant threats (e.g., development, timber harvest, animal agriculture, and cave visitation) and their interactions with local cave geology and species’ habitat preferences. Our virtual implementation of the SHELF protocol demonstrates the flexibility of this approach for conservation applications operating on budgets and timelines that can limit in‐person meetings of geographically dispersed experts.

Conservation Biology↗

USGS2020

A Bayesian framework for assessing extinction risk based on ordinal categories of population condition and projected landscape change

Many at-risk species lack standardized surveys across their range or quantitative data capable of detecting demographic trends. As a result, extinction risk assessments often rely on ordinal categories of risk based on explicit criteria or expert elicitation. This study demonstrates a Bayesian approach to assessing extinction risk based on this common data structure, using three freshwater mussel species being considered for listing under the US Endangered Species Act. The probability that a population is classified under each risk category was modeled as a function of projected landscape change using ordered probit regression, assuming observed categories reflect a latent, continuous probability of persistence. All three species were more likely than not (mean probability >0.5) to be classified as extirpated or low condition throughout their range based on effects of urban development and hydrologic alteration. Spatial variation in estimates revealed strongholds and high-risk areas relevant to conservation decision making. Projected change in probabilities of each risk category based on multiple land-use and climate models was generally small relative to high baseline risk resulting from past landscape changes. Assessing extinction risk based on probabilities of ordinal condition as a function of landscape patterns may provide a flexible and robust approach for many at-risk taxa by adjusting species' demographic criteria to match relative risk categories, following standardized criteria, or using expert elicitation for data-deficient species. This approach provides decision makers with a useful measure of uncertainty around ordinal classifications and provides a framework for estimating future risk based on projections of anthropogenic stressors.

Alabama, Georgia, Kentucky, North Carolina, South ↗